Automated renal cortical volume measurement for assessment of renal function in patients undergoing radical nephrectomy.

BACKGROUND: Renal volume change greatly affects renal function after nephrectomy. Although various measuring techniques were reported, no standard measuring method is available. In this study, we examined the computational automated volumetric method, and evaluated the volumetric change to assess the functional outcome in patients undergoing radical nephrectomy. We developed the predictive equation for postoperative renal function from volume alternation and validated the performance. METHODS: Thirty-two patients undergoing radical nephrectomy participated in this study. Renal volume was calculated using three different methods [ellipsoid method, conventional manual voxel count method for renal parenchyma (manual RPV), and automated voxel count method for renal cortex (automated RCV)] through newly developed imaging software. Statistical analysis was performed to evaluate the correlation between renal functional alternation 7 days after the nephrectomy and renal volumetric change. A simple predictive equation for the postoperative renal function by renal volume loss was developed and externally validated through another 12 cases. RESULTS: The automated RCV method had the strongest correlation between renal function alternation and RCV change (R = 0.82), than manual RPV (R = 0.69) and ellipsoid method (R = 0.50). Subsequently, a simple equation for postoperative renal function by renal volume alternation was developed: predicted postoperative estimated glomerular filtration rate (eGFR) from renal volume change = preoperative eGFR × (postoperative renal volume / preoperative renal volume). In the external validation cohort, automated RCV demonstrated the predictive performance of the constructed equations for renal function (R = 0.77). CONCLUSIONS: The computational automated RCV measurements is a simple estimation of renal functional outcome for patients undergoing radical nephrectomy.

Movement of target organs and anatomical landmarks caused by body position change during urological laparoscopic surgery.

INTRODUCTION: The aim of our study was to elucidate the impact of patients' physical characteristics on the movement of target organs and anatomical landmarks by comparing supine and lateral CT images. METHODS: This study consisted of 55 patients who underwent laparoscopic surgery in the lateral position. CT images of the area between the abdomen and pelvis were taken preoperatively with patients in both supine and lateral positions. We measured the moving distance of target organs and anatomical landmarks on the body surface used for access port settings. We investigated which covariates from patients' body composition most affected moving distance in correlation analysis. Then, using multiple linear regression analysis, we examined whether we could predict the movement of target organs and anatomical landmarks solely based on information obtained from supine CT images. RESULTS: The moving distance of both the hilum of the kidney and the outer edge of the rectus abdominis muscle were significantly associated with some physical characteristics. Multiple regression analysis showed that a larger visceral fat area could be a useful index for predicting the movement of the kidney toward the counter side. Lower CT density of back muscles and higher BMI could be useful indexes for predicting the movement of the rectus abdominis muscle. CONCLUSION: Our results suggested that body composition characteristics obtained from preoperative CT images can help predict the movement of target organs and anatomical landmarks used to determine proper port-site placement for laparoscopic surgery performed with the patient in the lateral position.